Bodies of water can become a significant hazard when navigating over terrain. Vehicles designed for terrestrial use, such as a car or truck, can be damaged when traversing through bodies of water. The ability for systems to automatically detect water through automated machine vision presents a unique challenge. Additionally, the ability to distinguish between merely water detected on the ground and a water hazard presents a further difficulty. Machine vision is the automated capture and processing of one or more images of a scene to detect features indicative of the scene. Machine vision is especially important for unmanned ground vehicle autonomous navigation systems as unmanned vehicles depend heavily upon machine vision for navigation over terrain.
Stereo cameras are a type of 3D image capture device with one or more separate image sensors that allow for multiple images to be captured of the same scene from different perspectives. By capturing images from different perspectives, the images captured by stereo cameras can be used to determine the distance between the camera sensor and features of a scene by reconciling the differences between the images captured by the multiple image sensors using the distance between each image sensor or from a single image sensor using the distance between the image sensor in two or more positions.
Cameras can capture many features of a scene. A color camera can capture the color in a scene as part of an image. Colors in an image can be represented as RGB images with the RGB color model in which colors in an image are represented as a combination of red, green and blue light. RGB images can be converted to a hue, saturation and value (HSV) color space. Conceptually, the HSV color space can be represented as a cone. The circumference of the circle is represented by hue values from 0 to 360 degrees on the circle side of the cone. Saturation and value (or brightness) have values of 0-1. Saturation can be represented by the distance from the center of the circle. Brightness can be represented by the distance along the vertical axis of the cone. The pointed end of the cone represents black or the absence of brightness. All colors are at their maximum brightness at the circle end of the cone.